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Identification of Working Conditions in Secondary Loop of Nuclear Power Plant Based on Improved Multiple PCA Modeling

机译:基于改进多个PCA建模的核电厂二次回路工作条件的识别

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摘要

Based on the angle and Euclidean distance similarity of the loading matrix, this paper reports on an improved principal component analysis (PCA) modeling method that is successfully applied to identify three different working conditions in the secondary loop of a nuclear power plant (NPP). First, a simulation platform of the secondary loop of the NPP is built in which three kinds of working conditions are set. Second, the multiple-PCA modeling method is used to construct the offline models. Finally, the effectiveness and superiority of the improved method is verified in the simulation platform.
机译:基于装载矩阵的角度和欧几里德距离相似性,本文报告了改进的主要成分分析(PCA)建模方法,其成功地应用于识别核电厂(NPP)中的三个不同的工作条件。首先,建立了NPP的次要循环的模拟平台,其中设定了三种工作条件。其次,使用多PCA建模方法来构造离线模型。最后,在仿真平台中验证了改进方法的有效性和优越性。

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